An application of Bayesian Active Learning to Vehicle dynamics performance design

Abstract

Drivability is a key aspect of vehicle dynamic performance and comprehensive evaluation is necessary for ensuring drivability quality as such complicated driver operation and vehicle behavior. Furthermore, vehicle control program would be complex for safe and secure vehicle dynamic performance. This paper proposes a novel automated drivability screening system. The proposed system is composed of automated evaluation sub-system and automated exploring sub-system. The automated evaluation sub-system is drivability evaluation by using driver model and PT-VRS equipment to mimic expert driver. The automated exploring sub-system is used to explore feasible region of design space described by control parameters and simulation conditions. To show effectiveness of the proposed system, an example is demonstrated by comparison to expert driver.